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@naveedharri · 收录于 1 周前

Meta Ads deep analysis covering Facebook and Instagram advertising. Evaluates 46 checks across Pixel/CAPI health, creative diversity and fatigue, account structure, and audience targeting. Includes Advantage+ assessment. Use when user says "Meta Ads", "Facebook Ads", "Instagram Ads", "Advantage+", or "Meta campaign".

适合你,如果你管理Facebook或Instagram广告账户,需要系统诊断投放问题。

/ 下载安装
ads-meta.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add naveedharri/benai-skills/ads-meta
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- naveedharri/benai-skills/ads-meta
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify naveedharri/benai-skills/ads-meta
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

技能原文 SKILL.md作者撰写 · MIT · 946a3d7

Meta Ads Deep Analysis

Process
  1. Collect Meta Ads data (Ads Manager export, Events Manager screenshot, EMQ scores)
  2. Read ads/references/meta-audit.md for full 46-check audit
  3. Read ads/references/benchmarks.md for Meta-specific benchmarks
  4. Read ads/references/scoring-system.md for weighted scoring
  5. Evaluate all applicable checks as PASS, WARNING, or FAIL
  6. Calculate Meta Ads Health Score (0-100)
  7. Generate findings report with action plan
What to Analyze
Pixel / CAPI Health (30% weight)
  • Meta Pixel installed and firing on all pages
  • Conversions API (CAPI) active (30-40% data loss without it post-iOS 14.5)
  • Event deduplication configured (event_id matching, ≥90% dedup rate)
  • Event Match Quality (EMQ) ≥8.0 for Purchase event
  • All standard events configured (ViewContent, AddToCart, Purchase, Lead)
  • Custom conversions created for non-standard events
  • Aggregated Event Measurement (AEM) configured for iOS
  • Domain verification completed
  • Server-side events include customer_information parameters
  • Pixel fires with correct currency and value parameters
Creative (30% weight)
  • ≥3 creative formats active (image, video, carousel, collection)
  • ≥5 creatives per ad set (Meta recommendation)
  • Creative fatigue detection: CTR drop >20% over 14 days = FAIL
  • Video creative: 15s max for Stories/Reels, 30s max for Feed
  • UGC/testimonial creative tested
  • Dynamic Creative Optimization (DCO) tested
  • Ad copy: headline under 40 chars, primary text under 125 chars
  • Creative refresh cadence: every 2-4 weeks for high-spend
Account Structure (20% weight)
  • Campaign Budget Optimization (CBO) vs Ad Set Budget (ABO) intentional
  • Campaign consolidation: ≤5 active campaigns per objective type
  • Learning phase health: <30% ad sets in "Learning Limited" (FAIL >50%)
  • Budget per ad set: ≥5x target CPA (minimum for learning phase exit)
  • Ad set audience overlap <30% (Audience Overlap tool)
  • Campaign naming conventions consistent and descriptive
  • Advantage+ Shopping Campaigns (ASC) active for e-commerce
  • Simplified campaign structure (fewer, larger ad sets preferred)
Audience & Targeting (20% weight)
  • Prospecting frequency (7-day): <3.0 (WARNING 3-5, FAIL >5)
  • Retargeting frequency (7-day): <8.0 (WARNING 8-12, FAIL >12)
  • Custom Audiences: website visitors, customer lists, engagement
  • Lookalike Audiences: multiple seed sizes tested (1%, 3%, 5%)
  • Advantage+ Audience tested vs manual targeting
  • Interest targeting: broad enough for algorithm optimization
  • Exclusions: purchasers excluded from prospecting, overlap managed
  • Location targeting reviewed for relevance
Advantage+ Assessment

If Advantage+ features are in use:

  • ASC (Shopping Campaigns): catalog connected, existing customer cap set
  • Advantage+ Audience: performance vs manual audience compared
  • Advantage+ Creative: enhancements enabled (text, brightness, music)
  • Advantage+ Placements: enabled (let Meta optimize placement mix)
  • Budget allocation: Advantage+ campaigns getting fair test budget
Special Ad Categories

If ads are in restricted categories:

  • Special Ad Category declared before campaign creation
  • Targeting restrictions verified (no ZIP, age 18-65+ only, no Lookalike)
  • Creative compliance with category-specific policies
  • Read ads/references/compliance.md for full requirements
EMQ Optimization Guide

| EMQ Score | Status | Action | |-----------|--------|--------| | 8.0-10.0 | Excellent | Maintain current setup | | 6.0-7.9 | Good | Add more customer_information parameters | | 4.0-5.9 | Fair | Implement CAPI, improve data quality | | <4.0 | Poor | Critical: CAPI + Enhanced Matching required |

Key parameters to maximize EMQ:

  • em (email) — highest match rate signal
  • ph (phone) — second highest match signal
  • fn, ln (first/last name) — improves match accuracy
  • ct, st, zp (city, state, zip) — geographic matching
  • external_id — CRM/user ID for cross-device matching
Key Thresholds

| Metric | Pass | Warning | Fail | |--------|------|---------|------| | EMQ (Purchase) | ≥8.0 | 6.0-7.9 | <6.0 | | Dedup rate | ≥90% | 70-90% | <70% | | CTR | ≥1.0% | 0.5-1.0% | <0.5% | | Creative formats | ≥3 | 2 | 1 | | Creatives per ad set | ≥5 | 3-4 | <3 | | Learning Limited | <30% | 30-50% | >50% | | Budget per ad set | ≥5x CPA | 2-5x CPA | <2x CPA |

Output
Meta Ads Health Score
Meta Ads Health Score: XX/100 (Grade: X)

Pixel / CAPI Health: XX/100  ████████░░  (30%)
Creative:            XX/100  ██████████  (30%)
Account Structure:   XX/100  ███████░░░  (20%)
Audience:            XX/100  █████░░░░░  (20%)
Deliverables
  • META-ADS-REPORT.md — Full 46-check findings with pass/warning/fail
  • EMQ improvement roadmap
  • Creative fatigue alerts (any creative with CTR declining >20%)
  • Quick Wins sorted by impact
  • Advantage+ adoption recommendations
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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